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ID 113245
Title Alternative
Emotion Recognition for Japanese Short Sentences Including Slangs
Author
Keywords
Youth Slang
Unknown Words
Bag of Concepts
Word Embedding
k-nearest neighbor algorithm
Maximum Entropy Method
Unsupervised Clustering
Content Type
Journal Article
Description
The growth of Internet communication sites such as weblogs and social networking sites brought younger people especially in teens and in their 20s to create new words and to use them very often. We prepared an emotion corpus by collecting weblog article texts including new words, analyzed the corpus statistically, and proposed a method to estimate emotions of the texts. Most slang words such as Youth Slang are too ambiguous in sense classification to be registered into the existing dictionaries such as thesaurus. To cope with these words, we created a large scale of Twitter corpus and calculated sense similarities between words. We proposed to convert unknown word to semantic class id so that we might be able to process the words that were not included in the learning data. For calculation similarities between words and converting the word into word cluster id, we used the word embedding algorithms such as word2vec, or GloVe. We defined this method as a method using Bag of Concepts as feature. As a result of the evaluation experiment using several classifiers, the proposed method was proved its robustness for unknown expressions.
Journal Title
Current Analysis on Instrumentation and Control
Publisher
Mesford Publisher
Volume
2019
Issue
2
Start Page
9
End Page
18
Published Date
2019-02-01
Rights
This is an open access article licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (Attribution-NonCommercial 4.0 International CC-BY-NC 4.0)(https://creativecommons.org/licenses/by-nc/4.0/deed.ja)
© 2018 Mesford Publisher INC
EDB ID
FullText File
language
eng
TextVersion
Publisher
departments
Science and Technology